We study scalable and efficient coordination and negotiation protocols for collaborative multi-agent systems (MAS). The coordination problem we address is multi-agent coalition formation in a fully decentralized, resource-bounded setting. More specifically, we design, analyze, optimize and experiment with the Maximal Clique based Distributed Coalition Formation (MCDCF) algorithm. We briefly des...

Several factors have meant that enterprises operate in an environment increasingly demanding in terms of flexibility and reactivity. The introduction of the entities resulting from Distributed Artificial Intelligence (DAI) and Multi-Agent Systems (MAS) in the management of enterprises prove to be an interesting technology to simulate and reproduce the collaborative and adaptive behavior of ente...

This thesis is motivated by the vast complexity of cooperative stochastic multi-agent planning, where agents can affect the transitions and rewards of one another, but in order to coordinate their interactions effectively, must account for the uncertainty in these actions. To combat this complexity, I exploit interaction structure in weakly-coupled problems to compute coordinated agent policies...

Conflict in multi-agent systems is ubiquitous. Research often focuses on the process of resolving conflicts between different agents. We call this the inter-agent conflict resolution process. However, in complex problem solving agents the process of resolving conflicts with other agents impacts local problem solving as well as deals made with other agents. This leads to the need for an intra-ag...

Coordination is one of the fundamental research issues in distributed artificial intelligence and multi-agent systems. Current multi-agent coalition formation methods present two limits: First, computation must be completely restarted when a change occurs. Second, utility functions of the agents are either global or aggregated. We present a new algorithm to cope with these limits. The first par...

Coordination is one of the fundamental research issues in distributed artificial intelligence and multi-agent systems. Current multi-agent coalition formation methods present two limits: First, computation must be completely restarted when a change occurs. Second, utility functions of the agents are either global or aggregated. We present a new algorithm to cope with these limits. The first par...

Physical agents, such as robots, are generally constrained in their communication capabilities. In a multi-agent system composed of physical agents, these constraints have a strong influence on the organization and the coordination mechanisms. Our multi-agent system is a satellite constellation for which we propose a collaboration method based on incremental coalition formation in order to opti...

This paper proposes a combined mechanism for coordinating agents in timed normative multi-agent systems. Timing constraints in a multi-agent system make it possible to force action execution to happen before certain time invariants are violated. In such multiagent systems we achieve coordination at two orthogonal levels with respect to states and actions. On the one hand, the behaviour of indiv...

Multi-agent planning is a core issue in the multi-agent systems field. In this work we focus on the coordination of multiple agents in a setting where agents are able to achieve individual goals that may be either independent, or necessary for the achievement of a global common goal. The agents are able to generate individual plans in order to achieve their own goals, but, as they share the sam...

We consider the scheduling method that allows to minimize traveling time of a AGV (and thus energy consumption) at each zones, while waiting automated guided vehicles (AGVs) and/or containers for pickup and delivery (PD) transfer points (TPs) installed between adjacent zones in tandem systems. Scheduling these systems is often not possible from single point by intelligent agent. Intead, has be ...